Matches in SemOpenAlex for { <https://semopenalex.org/work/W3015201166> ?p ?o ?g. }
- W3015201166 endingPage "1" @default.
- W3015201166 startingPage "1" @default.
- W3015201166 abstract "<p>Canopy fuel load, canopy bulk density and canopy base height are structural variables used to predict crown fire initiation and spread. Direct measurement of these variables is not functional, and they are usually estimated indirectly by modelling. Advances in fire behaviour modelling require accurate and landscape scale estimates of the complete vertical distribution of canopy fuels. The goal of the present study is to model the vertical profile of available canopy fuels in Scots pine stands by using data from the Spanish national forest inventory and low-density LiDAR data (0.5 first returns m<sup>–2</sup>) provided by Spanish PNOA project (Plan Nacional de Ortofotografía Aérea). In a first step, the vertical distribution of the canopy fuel load was modelled using the Weibull probability density function. In a second step, a system of models was fitted to relate the canopy variables to Lidar-derived metrics. Models were fitted simultaneously to compensate the effects of the inherent cross-model correlation between errors. Heteroscedasticity was also analyzed, but correction in the fitting process was not necessary. The estimated canopy fuel load profiles from LiDAR-derived metrics explained 41% of the variation in canopy fuel load in the analysed plots. The proposed models can be used to assess the effectiveness of different forest management alternatives for reducing crown fire hazard.</p>" @default.
- W3015201166 created "2020-04-17" @default.
- W3015201166 creator A5028111817 @default.
- W3015201166 creator A5031876776 @default.
- W3015201166 creator A5034763648 @default.
- W3015201166 creator A5037949849 @default.
- W3015201166 creator A5061585094 @default.
- W3015201166 creator A5067622148 @default.
- W3015201166 date "2019-06-27" @default.
- W3015201166 modified "2023-10-17" @default.
- W3015201166 title "Estimación de la distribución vertical de combustibles finos del dosel de copas en masas de Pinus sylvestris empleando datos LiDAR de baja densidad" @default.
- W3015201166 cites W131359794 @default.
- W3015201166 cites W1496824059 @default.
- W3015201166 cites W1592596486 @default.
- W3015201166 cites W1968987485 @default.
- W3015201166 cites W1976873454 @default.
- W3015201166 cites W1982817045 @default.
- W3015201166 cites W1991064179 @default.
- W3015201166 cites W2001618165 @default.
- W3015201166 cites W2009214675 @default.
- W3015201166 cites W2012824497 @default.
- W3015201166 cites W2023081345 @default.
- W3015201166 cites W2050161380 @default.
- W3015201166 cites W2054058513 @default.
- W3015201166 cites W2062682676 @default.
- W3015201166 cites W2066757235 @default.
- W3015201166 cites W2067077825 @default.
- W3015201166 cites W2084379146 @default.
- W3015201166 cites W2086888368 @default.
- W3015201166 cites W2106376825 @default.
- W3015201166 cites W2108626615 @default.
- W3015201166 cites W2110221217 @default.
- W3015201166 cites W2113242619 @default.
- W3015201166 cites W2113557105 @default.
- W3015201166 cites W2114228414 @default.
- W3015201166 cites W2117979964 @default.
- W3015201166 cites W2121111132 @default.
- W3015201166 cites W2151549592 @default.
- W3015201166 cites W2156812474 @default.
- W3015201166 cites W2159352923 @default.
- W3015201166 cites W2159690339 @default.
- W3015201166 cites W2162146569 @default.
- W3015201166 cites W2163324173 @default.
- W3015201166 cites W2165597803 @default.
- W3015201166 cites W2213612645 @default.
- W3015201166 cites W2282804752 @default.
- W3015201166 cites W2344535433 @default.
- W3015201166 cites W2430239505 @default.
- W3015201166 cites W2464863481 @default.
- W3015201166 cites W2478962215 @default.
- W3015201166 cites W2608260148 @default.
- W3015201166 cites W2616287920 @default.
- W3015201166 cites W2625014437 @default.
- W3015201166 cites W2738942205 @default.
- W3015201166 cites W2742967775 @default.
- W3015201166 cites W2751418581 @default.
- W3015201166 cites W2771694153 @default.
- W3015201166 cites W2779008628 @default.
- W3015201166 cites W2789265310 @default.
- W3015201166 cites W2793945807 @default.
- W3015201166 cites W2886694617 @default.
- W3015201166 cites W2912497241 @default.
- W3015201166 cites W2913372974 @default.
- W3015201166 cites W2919567221 @default.
- W3015201166 doi "https://doi.org/10.4995/raet.2019.11241" @default.
- W3015201166 hasPublicationYear "2019" @default.
- W3015201166 type Work @default.
- W3015201166 sameAs 3015201166 @default.
- W3015201166 citedByCount "9" @default.
- W3015201166 countsByYear W30152011662020 @default.
- W3015201166 countsByYear W30152011662021 @default.
- W3015201166 countsByYear W30152011662022 @default.
- W3015201166 countsByYear W30152011662023 @default.
- W3015201166 crossrefType "journal-article" @default.
- W3015201166 hasAuthorship W3015201166A5028111817 @default.
- W3015201166 hasAuthorship W3015201166A5031876776 @default.
- W3015201166 hasAuthorship W3015201166A5034763648 @default.
- W3015201166 hasAuthorship W3015201166A5037949849 @default.
- W3015201166 hasAuthorship W3015201166A5061585094 @default.
- W3015201166 hasAuthorship W3015201166A5067622148 @default.
- W3015201166 hasBestOaLocation W30152011661 @default.
- W3015201166 hasConcept C101000010 @default.
- W3015201166 hasConcept C105795698 @default.
- W3015201166 hasConcept C121332964 @default.
- W3015201166 hasConcept C166957645 @default.
- W3015201166 hasConcept C173291955 @default.
- W3015201166 hasConcept C199343813 @default.
- W3015201166 hasConcept C205649164 @default.
- W3015201166 hasConcept C2778400979 @default.
- W3015201166 hasConcept C2779128174 @default.
- W3015201166 hasConcept C2781353100 @default.
- W3015201166 hasConcept C2910048773 @default.
- W3015201166 hasConcept C33923547 @default.
- W3015201166 hasConcept C39432304 @default.
- W3015201166 hasConcept C51399673 @default.
- W3015201166 hasConcept C59822182 @default.
- W3015201166 hasConcept C62649853 @default.
- W3015201166 hasConcept C71924100 @default.